Probabilistic fire-danger forecasting: A framework for week-two forecasts using statistical post-processing techniques and the Global ECMWF Fire Forecast System (GEFF)

Details

• Journal Title:
  Weather and Forecasting
• Personal Author:
  Worsnop, Rochelle P. ; Scheuerer, Michael ; Di Giuseppe, Francesca ; Barnard, Christopher ; Hamill, Thomas M. ; Vitolo, Claudia
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; PSL (Physical Sciences Laboratory) ; CIRES (Cooperative Institute for Research in Environmental Sciences) ; NWS (National Weather Service) ; CPC (Climate Prediction Center)
• Description:
  Wildfire guidance two weeks ahead is needed for strategic planning of fire mitigation and suppression. However, fire forecasts driven by meteorological forecasts from numerical weather prediction models inherently suffer from systematic biases. This study uses several statistical-postprocessing methods to correct these biases and increase the skill of ensemble fire forecasts over the contiguous United States 8–14 days ahead. We train and validate the postprocessing models on 20 years of European Centre for Medium-Range Weather Forecasts (ECMWF) reforecasts and ERA5 reanalysis data for 11 meteorological variables related to fire, such as surface temperature, wind speed, relative humidity, cloud cover, and precipitation. The calibrated variables are then input to the Global ECMWF Fire Forecast (GEFF) system to produce probabilistic forecasts of daily fire indicators, which characterize the relationships between fuels, weather, and topography. Skill scores show that the postprocessed forecasts overall have greater positive skill at days 8–14 relative to raw and climatological forecasts. It is shown that the postprocessed forecasts are more reliable at predicting above- and below-normal probabilities of various fire indicators than the raw forecasts and that the greatest skill for days 8–14 is achieved by aggregating forecast days together.
• Keywords:
  Forecasting Forest Fires Probability Forecasts (Meteorology) Forest Fires Probability Forecasts (Meteorology) HIndcasts
• Source:
  Weather and Forecasting, 36(6), 2113-2125
• DOI:
  https://doi.org/10.1175/WAF-D-21-0075.1
• Document Type:
  Journal Article
• Funding:
  Grant no. NA17OAR4320101
• Rights Information:
  Other
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha256:9f581206809bcdf4701f5369b28002c4f9b167dc41c250bc06dd335e81e9564f
• Download URL:
  https://repository.library.noaa.gov/view/noaa/44563/noaa_44563_DS1.pdf
• File Type:
  [PDF - 1.57 MB ]